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October 12 2012, Apache Lucene‚ 4.0 available.
The Lucene PMC is pleased to announce the release of Apache Lucene 4.0
Apache Lucene is a high-performance, full-featured text search engine
library written entirely in Java. It is a technology suitable for
nearly any application that requires full-text search, especially
cross-platform.
This release contains numerous bug fixes, optimizations, and
improvements, some of which are highlighted below. The release is
available for immediate download at:
http://lucene.apache.org/core/mirrors-core-latest-redir.html
See the CHANGES.txt file included with the release for a full list of details.
Lucene 4.0 Release Highlights:
* The index formats for terms, postings lists, stored fields, term
vectors, etc are pluggable via the Codec api. You can select from the
provided implementations or customize the index format with your own
Codec to meet your needs.
* Similarity has been decoupled from the vector space model (TF/IDF).
Additional models such as BM25, Divergence from Randomness, Language
Models, and Information-based models are provided (see
http://www.lucidimagination.com/blog/2011/09/12/flexible-ranking-in-lucene-4).
* The new doc values feature stores typed values per-document. It
can be used for custom scoring factors (accessible via Similarity),
for pre-sorted Sort values, and more.
* IndexWriter now flushes segments to disk concurrently, when the
application uses multiple threads for indexing, resulting in
substantial performance improvements (see
http://blog.mikemccandless.com/2011/05/265-indexing-speedup-with-lucenes.html).
* Per-document normalization factors ("norms") are no longer limited
to a single byte. Similarity implementations can use any DocValues
type to store norms.
* New index statistics have been added, including the number of
tokens for a term or field, number of postings for a field, and number
of documents with a posting for a field. These support additional
scoring models (see
http://blog.mikemccandless.com/2012/03/new-index-statistics-in-lucene-40.html).
* A new default term dictionary/index (BlockTree) indexes shared
prefixes instead of every n'th term. This is not only more time- and
space- efficient, but can avoid going to disk at all for terms that do
not exist in certain cases. Alternative term dictionary implementions
are provided and pluggable via the Codec api.
* Indexed terms are no longer limited to UTF-16 char sequences; they
can now be any binary value encoded as byte arrays. By default, text
terms are encoded as UTF-8 bytes. Sort order of terms is defined by
their binary value, which is identical to UTF-8 (Unicode code point)
sort order.
* Substantially faster performance when using a Filter during searching.
* File-system based directories can rate-limit the IO (MB/sec) of
merge threads, to reduce IO contention between merging and searching
threads.
* A number of alternative Codecs and components have been added:
"Appending" works with append-only filesystems (such as Hadoop DFS),
"Memory" writes the entire terms+postings as an FST read into RAM (see
http://blog.mikemccandless.com/2011/06/primary-key-lookups-are-28x-faster-with.html),
"Pulsing" inlines the postings for low-frequency terms into the term
dictionary (see
http://blog.mikemccandless.com/2010/06/lucenes-pulsingcodec-on-primary-key.html),
"SimpleText" writes all files in plain-text for easy
debugging/transparency (see
http://blog.mikemccandless.com/2010/10/lucenes-simpletext-codec.html),
"Bloom" uses a bloom filter to sometimes avoid disk seeks when looking
up terms, "Direct" holds all postings as simple byte[] and int[] for
very fast performance at the cost of very high RAM consumption,
"Block" use a new index layout and compression scheme for improved
performance, among others.
* Term offsets can be optionally encoded into the postings lists and
retrieved per-position.
* A new AutomatonQuery returns all documents containing any term
matching a provided finite-state automaton (see
http://www.slideshare.net/otisg/finite-state-queries-in-lucene).
* FuzzyQuery is 100-200 times faster than in past releases (see
http://blog.mikemccandless.com/2011/03/lucenes-fuzzyquery-is-100-times-faster.html).
* A new spell checker, DirectSpellChecker, finds possible corrections
directly against the main search index without requiring a separate
index.
* Various in-memory data structures such as the term dictionary and
FieldCache are represented more efficiently with less object overhead
(see http://blog.mikemccandless.com/2010/07/lucenes-ram-usage-for-searching.html).
* All search logic is now required to work per segment, IndexReader
was therefore refactored to differentiate between atomic and composite
readers (see http://blog.thetaphi.de/2012/02/is-your-indexreader-atomic-major.html).
* Lucene 4.0 provides a modular API, consolidating components such as
Analyzers and Queries that were previously scattered across Lucene
core, contrib, and Solr. These modules also include additional
functionality such as UIMA analyzer integration and a completely
reworked spatial search implementation.
Noteworthy changes since 4.0-BETA:
* A new "Block" PostingsFormat offering improved search performance
and index compression. This will likely become the default format in a
future release. (see
http://blog.mikemccandless.com/2012/08/lucenes-new-blockpostingsformat-thanks.html).
* All non-default codec implementations were moved to a separated
codecs module. Just add lucene-codecs-4.0.0.jar to your classpath to
test these out.
* Payloads can be optionally stored on the term vectors.
* Many bugfixes and optimizations.
Please read CHANGES.txt and MIGRATE.txt for a full list of new
features and notes on upgrading. Particularly, the new apis are not
compatible with previous versions of Lucene, however, file format
backwards compatibility is provided for indexes from the 3.0 series
and the 4.0-alpha and -beta releases.
Please report any feedback to the mailing lists
(http://lucene.apache.org/core/discussion.html)
Note: The Apache Software Foundation uses an extensive mirroring
network for distributing releases. It is possible that the mirror you
are using may not have replicated the release yet. If that is the
case, please try another mirror. This also goes for Maven access.
Happy searching,
Apache Lucene/Solr Developers
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